By the same authors

Towards autonomic cloud services engineering via intention workflow model

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Published copy (DOI)

Author(s)

  • Thar Baker
  • Omer F. Rana
  • Radu Calinescu
  • Rafael Tolosana-Calasanz
  • José Ángel Bañares

Department/unit(s)

Publication details

Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DatePublished - 30 Oct 2013
Pages212-227
Volume8193
Original languageEnglish

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8193 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Abstract

In recent years, the rise and rapid adoption of cloud computing has acted as a catalyst for research in related fields: virtualization, distributed and service-oriented computing to name but a few. Whilst cloud computing technology is rapidly maturing, many of the associated long-standing socio-technical challenges including the dependability of cloud-based service composition, services manageability and interoperability remain unsolved. These can be argued to slow down the migration of serious business critical applications to the cloud model. This paper reports on progress towards the development of a method to generate cloud-based service compositions from requirements metadata. The paper presents a formal approach that uses Situation Calculus to translate service requirements into an Intention Workflow Model (IWM). This IWM is then used to generate autonomic cloud service composition. The Petshop benchmark is used to illustrate and evaluate the proposed method.

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